Affiliation:
1. Shanghai Tianma Microelectronics Co., Ltd. Shanghai China
2. School of Integrated Circuits Nanjing University Suzhou China
3. Shanghai Jiao Tong University Shanghai China
Abstract
As a widely acknowledged next‐generation display technology in the display industry, Micro LED has its advantages, but also faces significant issues with the mura phenomenon. Moreover, traditional Demura algorithms have numerous limitations when applied to Micro LEDs, leading to limited compensation effects. This paper first introduces the specific problems of current Demura algorithms in Micro LED applications and proposes a Demura algorithm based on Generative Adversarial Networks (GANs) from deep learning, targeted to address these issues. Subsequently, it delves into the principles of Generative Adversarial Networks, their integration with Demura algorithms, and finally, analyzes and summarizes the actual usage effects. The paper concludes with an analysis and outlook on potential improvements and future applications of the model.
Reference6 articles.
1. Driving of Micro-LED and OLED Mixed Integrated Display Devices with Opposite Polarity Structures;He Shuang;Liquid Crystals and Displays,2023
2. 17.2: Optical Compensation Study of MicroLED with Pure PAM Driving Scheme
3. Generative adversarial networks[J];Goodfellow I;Communications of the ACM,2020
4. Occluded face restoration based on Generative Adversarial Networks[C]//2020 3rd International Conference on Advanced Electronic Materials;Zhang M.;Computers and Software Engineering (AEMCSE). IEEE,2020
5. Banach Wasserstein Gan[J];Adler J;Advances in neural information processing systems,2018